class_docstr: Transformer-based language model on multiple streams of codes.
  
  Args:
      pattern_provider (CodebooksPatternProvider): Pattern provider for codebook interleaving.
      condition_provider (MusicConditioningProvider): Conditioning provider from metadata.
      fuser (ConditionFuser): Fuser handling the fusing of conditions with language model input.
      n_q (int): Number of parallel streams to model.
      card (int): Cardinality, vocabulary size.
      dim (int): Dimension of the transformer encoder.
      num_heads (int): Number of heads for the transformer encoder.
      hidden_scale (int): Scale for hidden feed forward dimension of the transformer encoder.
      norm (str): Normalization method.
      norm_first (bool): Use pre-norm instead of post-norm.
      emb_lr (float, optional): Embedding-specific learning rate.
      bias_proj (bool): Use bias for output projections.
      weight_init (str, optional): Method for weight initialization.
      depthwise_init (str, optional): Method for depthwise weight initialization.
      zero_bias_init (bool): If true and bias in Linears, initialize bias to zeros.
      cfg_dropout (float): Classifier-free guidance dropout.
      cfg_coef (float): Classifier-free guidance coefficient.
      attribute_dropout (dict): Attribute dropout probabilities.
      two_step_cfg (bool): Whether to run classifier free-guidance with 2 distinct steps.
      **kwargs: Additional parameters for the transformer encoder.
code: def special_token_id(self) -> int:
      return self.card
  
imports: from dataclasses import dataclass
  from functools import partial
  import logging
  import math
  import typing
  import torch
  from torch import nn
  from ..utils import utils
  from ..modules.streaming import StreamingModule, State
  from ..modules.transformer import StreamingTransformer, create_norm_fn
  from ..modules.conditioners import ConditionFuser, ClassifierFreeGuidanceDropout, AttributeDropout, ConditioningProvider, ConditioningAttributes, ConditionType
  from ..modules.codebooks_patterns import CodebooksPatternProvider
  from ..modules.activations import get_activation_fn
label_desc: Use image node_id 3 for calling the LMModel obj's underlying member method code with example usage: obj.special_token_id() and returns: self